Hi,
I'm currently struggling with some DEseq2 analyses of RNA-seq data. I'm told this should be pretty 'easy' and just follow the vignette, but I'm finding some difficulties.
My situation is that everything seems to be working. I'm coming from this raw counts for a gene:
A_1: 900
A_2: 134
B_1: 14825
B_2: 8312
These are the normalized counts:
A_1: 784.8627
A_2: 203.5322
B_1: 19424.8883
B_2: 4966.5403
The sample table includes condition (A,A,B,B) and replicate (1,1,2,2). The design has been:
design = ~ condition + replicate
And the results have been obtained with:
results(dds,contrast=c("condition","A","B"))
How is it possible that for the gene with the counts above, I'm getting a positive log2FoldChange? When it should be more highly expressed in condition B according to the counts?
log2 fold change (MLE): condition A vs B
Wald test p-value: condition A vs B
baseMean: 6344.96
log2FoldChange: 1.95771
lfcSE: 0.373301
stat: 5.2443
pvalue: 1.56873e-07
padj: 2.76881e-05
I must be missing something. Can anyone point me to the right direction or to some documentation apart from the vignette? I'm aware the replicates are showing variability (they're far in the PCA). Could that be causing this?
Thank you very much for the help
3 answers
It looks to me like your coding of replicate is wrong. Should replicate not be (1,2,1,2)? Its also not a good idea to use numbers for experimental factors in a model like this, as DESeq might interpret you as saying the "replicate" experimental factor is twice as high in replicate 1 as replicate 2. Using your design above, it would account for this in the model, and might be, effectively, dividing the sample Bs by two.
So, what happens if you code replicate at c("R1", R2", "R1", "R2")?
This fully resolves the issue?
No inconvenience at all, nanoide.
If you want to control for the effect of Replicates, shouldn't the design be ~ replicate + condition?
I am basing this on the following workflow from Mike Love et al.
The simplest design formula for differential expression would be
~ condition, where condition is a column in colData(dds) that specifies which of two (or more groups) the samples belong to. For the airway experiment, we will specify~ cell + dexmeaning that we want to test for the effect of dexamethasone (dex) controlling for the effect of different cell line (cell).
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